2026-04-20T21:56:48Zhttps://ebiltegia.mondragon.edu/oai/requestoai:ebiltegia.mondragon.edu:20.500.11984/11842024-03-06T08:38:58Zcom_20.500.11984_1143col_20.500.11984_1148
On the Feasibility of Distinguishing Between Process Disturbances and Intrusions in Process Control Systems using Multivariate Statistical Process Control
Iturbe, Mikel
Garitano, Iñaki
Zurutuza, Urko
Uribeetxeberria, Roberto
Camacho, José
process control systems
Multivariate Statistical Process Control
Tennessee-Eastman
Process Control Systems (PCSs) are the operat-ing core of Critical Infrastructures (CIs). As such, anomalydetection has been an active research field to ensure CInormal operation. Previous approaches have leveraged networklevel data for anomaly detection, or have disregarded theexistence of process disturbances, thus opening the possibility of mislabelling disturbances as attacks and vice versa. In thispaper we present an anomaly detection and diagnostic systembased on Multivariate Statistical Process Control (MSPC), thataims to distinguish between attacks and disturbances. For this end, we expand traditional MSPC to monitor process leveland controller level data. We evaluate our approach using the Tennessee-Eastman process. Results show that our approachcan be used to distinguish disturbances from intrusions to acertain extent and we conclude that the proposed approach canbe extended with other sources of data for improving results.
2019-04-08T12:05:33Z
2019-04-08T12:05:33Z
2016
http://purl.org/coar/resource_type/c_c94f
978-1-5090-3688-2
https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=123680
https://hdl.handle.net/20.500.11984/1184
eng
© 2016 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
IEEE